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How to use Vue and NetEase Cloud API to develop a personalized music recommendation system

In recent years, music recommendation systems have played an increasingly important role in various music platforms. In order to meet the personalized needs of users, the recommendation system needs to make accurate recommendations based on the user's preferences and behavior. In this article, we will introduce how to use Vue and NetEase Cloud API to develop a personalized music recommendation system.

1. Preparation

Before we start, we need to prepare the following tools and environment:

  1. Vue.js: a popular JavaScript framework for building Interactive web interface.
  2. NetEase Cloud API: An open API provided by NetEase Cloud Music for obtaining music data.
  3. Editor: such as Visual Studio Code, used for writing code.

2. Create a Vue project

First, we need to create a Vue project. Execute the following command in the command line:

$ vue create music-recommendation

Follow the prompts and select the default options. After the creation is completed, enter the project directory.

3. Install dependencies

In the project directory, execute the following command to install the required dependencies:

$ npm install axios

4. Obtain the NetEase Cloud API key

In order to call the NetEase Cloud API, we need to obtain the API key. Please visit [NetEase Cloud Music Developer Platform](https://music.163.com/) to register and create an application. On the application details page, you can obtain the API key.

5. Write code

  1. Create a folder named services in the src directory, and create a file named music.js in it. This file will be used to encapsulate code related to NetEase Cloud API. In music.js, we need to import axios and set its default request address and headers, as follows:
import axios from 'axios';

// 设置默认请求地址
axios.defaults.baseURL = 'https://api.music.163.com';

// 设置默认请求头
axios.defaults.headers = {
  'Content-Type': 'application/x-www-form-urlencoded',
};

// 导出axios实例
export default axios;
  1. Create a folder named components in the src directory , create a file named Recommendation.vue in it. This file will be used to display the music recommendation results. In Recommendation.vue, we need to import music.js and use it to call NetEase Cloud API to obtain music recommendation results, as shown below:
<template>
  <div>
    <h1 id="音乐推荐">音乐推荐</h1>
    <ul>
      <li v-for="song in songs" :key="song.id">
        {{ song.name }} - {{ song.artist }}
      </li>
    </ul>
  </div>
</template>

<script>
import music from '@/services/music';

export default {
  data() {
    return {
      songs: [],
    };
  },
  mounted() {
    this.getRecommendation();
  },
  methods: {
    async getRecommendation() {
      try {
        const response = await music.get('/v1/recommend/songs');
        this.songs = response.data.songs;
      } catch (error) {
        console.error(error);
      }
    },
  },
};
</script>

6. Use components

  1. In App.vue, import the Recommendation component and use it in the template as follows:
<template>
  <div id="app">
    <Recommendation />
  </div>
</template>

<script>
import Recommendation from '@/components/Recommendation';

export default {
  name: 'App',
  components: {
    Recommendation,
  },
};
</script>
  1. In App.vue, add some in the style tag The basic style is as follows:
<style>
#app {
  text-align: center;
}

h1 {
  margin-top: 50px;
}

ul {
  list-style: none;
  padding: 0;
  margin-top: 20px;
}

li {
  margin-bottom: 10px;
}
</style>

7. Start the project

Use the following command to start the project:

$ npm run serve

Visit http:// in the browser localhost:8080, you can see the music recommendation results.

Summary

This article introduces how to use Vue and NetEase Cloud API to develop a personalized music recommendation system. By encapsulating the interaction logic with NetEase Cloud API, we can easily obtain the music recommendation results and display them using Vue components. Of course, in addition to music recommendations, we can also design more personalized functions based on user behavior and preferences, such as song search, playlist recommendations, etc. I hope this article is helpful to you, and I wish you happy development!

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